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The Treebagger give different results in 2012a and 2013a

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xq
xq el 19 de Abr. de 2013
I used
B = TreeBagger(NTrees(j),train_feats',train_labels');
and
Y = predict(B,test_feats');
to classification, in train_feats each column is a sample,the train_labels total of 30 categories,label from 0 to 29.
when I run the code in matlab 2012a the accuracy almost 90%,but when i update to 2013a the accuracy is less than 1%. The data and the code are intact, why the result is so different?
Does anyone have an explanation?

Respuesta aceptada

Tom Lane
Tom Lane el 23 de Abr. de 2013
This might be the explanation, and it includes a suggestion of how to avoid the problem:
http://www.mathworks.com/support/bugreports/927692
  1 comentario
xq
xq el 23 de Abr. de 2013
Thank you so much for your answer and advice. The answer is exactly the problem. I change the labels from ordinals to chars:
NewLabels{i} = num2str(labels(i));
problem solved!
Thank you again for your help.

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